Cognitive network

About: Cognitive network is a research topic. Over the lifetime, 4213 publications have been published within this topic receiving 107093 citations.

Capacity scaling of general cognitive networks

Abstract: There has been recent interest within the networking research community to understand how performance scales in cognitive networks with overlapping n primary nodes and m secondary nodes. Two important metrics, i.e., throughput and delay, are studied in this paper. We first propose a simple and extendable decision model, i.e., the hybrid protocol model, for the secondary nodes to exploit spatial gap among primary transmissions for frequency reuse. Then, a framework for general cognitive networks is established based on the hybrid protocol model to analyze the occurrence of transmission opportunities for secondary nodes. We show that if the primary network operates in a generalized TDMA fashion, or employs a routing scheme such that traffic flows choose relays independently, then the hybrid protocol model suffices to guide the secondary network to achieve the same throughput and delay scaling as a standalone network without harming the performance of the primary network, as long as the secondary transmission range is smaller than the primary range in order. Our approach is general in the sense that we only make a few weak assumptions on both networks, and therefore it obtains a wide variety of results. We show secondary networks can obtain the same order of throughput and delay as standalone networks when primary networks are classic static networks, networks with random walk mobility, hybrid networks, multicast networks, CSMA networks, networks with general mobility, or clustered networks. Our work presents a relatively complete picture of the performance scaling of cognitive networks and provides fundamental insight on the design of them.

JENNA: a jamming evasive network-coding neighbor-discovery algorithm for cognitive radio networks [Dynamic Spectrum Management]

Abstract: Cognitive radios operate in a particularly challenging wireless environment. Besides the strict requirements imposed by opportunistic coexistence with licensed users, cognitive radios may have to deal with other concurrent (either malicious or selfish) cognitive radios that aim at gaining access to the available spectrum resources with no regard to fairness or other behavioral etiquettes. By taking advantage of their highly flexible RF front-ends, they are able to mimic a licensed user's behavior or simply jam a given channel with high power. This way these concurrent users (jammers) are capable of interrupting or delaying the neighbor discovery process initiated by a cognitive radio, which is interested in using a portion of the available spectrum for its own data communications. To solve this problem we propose a Jamming Evasive Network-coding Neighbor-Discovery Algorithm (JENNA), which ensures complete neighbor discovery for a cognitive radio network in a distributed and asynchronous way. We compare the proposed algorithm with baseline schemes that represent existing solutions, and validate its feasibility in a single-hop cognitive radio network.

Interference Reduction by Beamforming in Cognitive Networks

Abstract: We consider beamforming in a cognitive network with multiple primary users and secondary users sharing the same spectrum. In particular, we assume that each secondary transmitter has Nt antennas and transmits data to its single- antenna receiver using beamforming. The beamformer is designed to maximize the cognitive user's signal-to-interference ratio (SIR), defined as the ratio of the received signal power at the desired cognitive receiver to the total interference created at all the primary receivers. Using mathematical tools from random matrix theory, we derive both lower and upper bounds on the average interference at the primary receivers and the average SIR of the cognitive user. We further analyze and prove the convergence of these two performance measures asymptotically as the number of antennas Nt or primary users Nt increases. Specifically, the average interference per primary receiver converges to the expected value of the path loss in the network whereas the average SIR of the secondary user decays as 1/c when c = Np/Nt rarr infin. In the special case of Nt = Np, the average total interference approaches 0 and the average SIR approaches infin.

The OSI 95 Connection-Mode Transport Service: The Enhanced QoS

Abstract: During the last ten years, tremendous changes have taken place in the communication environments. First, there has been a continuous increase in network performance that has led, for instance, to increasingly high access data rates available in the lower layers. Furthermore, the changes in the offered network services have raised the issue of providing, at the transport level, services already provided at the subnetwork level, such as multicast or synchronous services for example. With the arrival of new applications, such as multimedia or client/server applications, a widening of the application requirements has also been observed. It is this evolving environment that has been at the origin of the ESPRIT II Project OSI 95. An important task in the framework of this project is the definition of an enhanced Transport Service taking account of the aforementioned evolutions. The enhanced Transport Service specified for OSI 95 consists of several types of service. The paper presents the connection-mode Transport Service. We focus mainly on the following original features of our connection-mode service: a new semantics for QoS parameters and the associated negotiation and re-negotiation.. Keyword Codes: C.2.1; C.2.2; C.2.m

Resource Allocation with Flexible Channel Cooperation in Cognitive Radio Networks

Abstract: We study the resource allocation problem in an OFDMA based cooperative cognitive radio network, where secondary users relay data for primary users in order to gain access to the spectrum. In light of user and channel diversity, we first propose FLEC, a novel flexible channel cooperation scheme. It allows secondary users to freely optimize the use of channels for transmitting primary data along with their own, in order to maximize performance. Further, we formulate a unifying optimization framework based on Nash bargaining solutions to fairly and efficiently allocate resources between primary and secondary networks, in both decentralized and centralized settings. We present an optimal distributed algorithm and a sub-optimal centralized heuristic, and verify their effectiveness via realistic simulations. Under the same framework, we also study conventional identical channel cooperation as the performance benchmark, and propose algorithms to solve the corresponding optimization problems. KEYWORDS—Cognitive radio, Cooperative Communication, Resource Allocation, Nash bargaining solutions, OFDMA.